Article
Chemistry, Analytical
Felipe Raposo Passos Mansoldo, Rafael Garrett, Veronica da Silva Cardoso, Marina Amaral Alves, Alane Beatriz Vermelho
Summary: Genetic information and computational tools are used in various fields to analyze and classify data. Recently, the chemical ontology of metabolites has become computationally obtainable, allowing for the application of genetic taxonomy methods in the field of metabolite classification. Community ecology tools, with their mature methods and established statistical tools, are well-suited for this adaptation. The Metabology approach presented in this study transforms metabolites into an ecosystem based on chemical ontology. The applicability of this approach is demonstrated using publicly available data from a metabolomics study of human plasma and an untargeted metabolomics study of a fungal pathogen.
ANALYTICA CHIMICA ACTA
(2022)
Article
Automation & Control Systems
Sunder Ali Khowaja, Parus Khuwaja, Kapal Dev, Ik Hyun Lee, Wali Ullah Khan, Weizheng Wang, Nawab Muhammad Faseeh Qureshi, Maurizio Magarini
Summary: This article proposes an efficient and secure data sharing scheme for vehicular social networks using community segmentation and a blockchain-based framework. Experimental results show that the proposed scheme achieves good performance in terms of security, computational complexity, and throughput.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Editorial Material
Biotechnology & Applied Microbiology
Andreas Gollner, Markus Koester, Paul Nicklin, Thomas Trieselmann, Elliott Klein, Jaromir Vlach, Claudia Heine, Marc Grundl, Juergen Ramharter, David Wyatt, Menorca Chaturvedi, Alessio Ciulli, Katharine C. Carter, Susanne Mueller, Daniel Bischoff, Peter Ettmayer, Eric Haaksma, Juergen Mack, Darryl McConnell, Dirk Stenkamp, Harald Weinstabl, Matthias Zentgraf, Clive R. Wood, Florian Montel
Summary: Pharmacological probes are essential for studying disease biology and developing new therapies. The Boehringer Ingelheim open innovation portal opnMe.com addresses the issue of using inadequate molecules by sharing extensively validated probes with the scientific community.
NATURE REVIEWS DRUG DISCOVERY
(2022)
Article
Genetics & Heredity
Elizabeth Wohler, Renan Martin, Sean Griffith, Eliete da S. Rodrigues, Corina Antonescu, Jennifer E. Posey, Zeynep Coban-Akdemir, Shalini N. Jhangiani, Kimberly F. Doheny, James R. Lupski, David Valle, Ada Hamosh, Nara Sobreira
Summary: With the advancement of whole exome and genome sequencing, tools for disease gene discovery have become crucial. PhenoDB, GeneMatcher, and VariantMatcher have been developed to facilitate data sharing and analysis, connecting genes to phenotypic traits worldwide. Further development of these platforms will enhance variant analysis and aid in novel disease-gene discovery.
ORPHANET JOURNAL OF RARE DISEASES
(2021)
Article
Computer Science, Theory & Methods
Francesca Cerruto, Stefano Cirillo, Domenico Desiato, Simone Michele Gambardella, Giuseppe Polese
Summary: Social networks have a significant impact on people's daily lives as a vast source of information, but privacy issues have always been a challenging problem. This research aims to evaluate the privacy protection provided by social networks by analyzing the data of users from different platforms. Utilizing image recognition techniques, a tool was built to extract personal data from users' profiles. By comparing the mandatory registration data, publicly accessible data, and data obtained through analysis, it was found that users' data can be easily accessed, leading to privacy violations. The study aims to enhance users' awareness of managing and sharing social network data.
JOURNAL OF BIG DATA
(2022)
Article
Chemistry, Analytical
David Sarramia, Alexandre Claude, Francis Ogereau, Jeremy Mezhoud, Gilles Mailhot
Summary: This article presents a platform called CEBA for environmental data, aiming to fill the gap in regional institutional platforms for sharing, searching, storing, and visualizing heterogeneous scientific data. The platform is characterized by its user-friendliness and accessibility to all types of data. Using a data lake approach, an on-premise solution has been developed to provide cloud services and open data access, with comprehensive support for managing geographic coordinates.
Article
Ecology
Jordan D. A. Hart, Daniel W. Franks, Lauren J. N. Brent, Michael N. Weiss
Summary: The study introduces a method for computing network correlation using a Gamma-Poisson model, and shows that the level of network correlation affects the power of nodal regression analyses. It also demonstrates the positive impact of social differentiation, mean social event rate, and harmonic mean of sampling times on network correlation strength.
METHODS IN ECOLOGY AND EVOLUTION
(2022)
Article
Chemistry, Analytical
Antonio Rivera, Pedro Ponce, Omar Mata, Arturo Molina, Alan Meier
Summary: Current weather monitoring systems often remain out of reach for small-scale users and local communities due to their high costs and complexity. This paper introduces a cost-effective and easy-to-use local weather station that utilizes low-cost sensors to provide efficient in-site measurements of various environmental parameters. It demonstrates the station's capability to remotely monitor these variables and provide accurate forecasts, making environmental monitoring more accessible and user-friendly.
Review
Biochemistry & Molecular Biology
Chao Yang, Debajyoti Chowdhury, Zhenmiao Zhang, William K. Cheung, Aiping Lu, Zhaoxiang Bian, Lu Zhang
Summary: The study thoroughly investigates computational tools for metagenomic sequencing, including assembly, binning, gene prediction, functional annotation, classification, and profiling. The tools are categorized based on their functional background, with core algorithms and information introduced for a comparative view. Emphasis is placed on computational requirements and guidance for selecting the most efficient tools.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2021)
Article
Public, Environmental & Occupational Health
Sylvia Kiwuwa-Muyingo, Jim Todd, Tathagata Bhattacharjee, Amelia Taylor, Jay Greenfield
Summary: The COVID-19 pandemic has driven the use of AI and DS innovations in data collection and aggregation. INSPIRE utilizes the OMOP CDM implemented in the cloud as a PaaS for COVID-19 data, allowing for optimization of public health response and patient recovery. INSPIRE-PEACH harmonizes and analyzes data from Kenya and Malawi using AI technologies, enabling the discovery and evaluation of COVID-19 pathways.
FRONTIERS IN PUBLIC HEALTH
(2023)
Article
Green & Sustainable Science & Technology
Pan Zhang, Da Zhao, Zhi Qiao, Yu Xiong, Jiamin Liang
Summary: This paper aims to study the strategic effects of manufacturers' environmental innovation on supply chain information sharing. The analysis shows that after conducting environmental innovation, the retailer may fully or partially share demand information for free. The retailer is more willing to share information voluntarily in Case T, compared to Case O.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Computer Science, Artificial Intelligence
Ifrah Raoof, Manoj Kumar Gupta
Summary: In this paper, a brain-computer interface technology using generative adversarial networks for data augmentation is presented. By incorporating conditional input labels and temporal generative adversarial networks, the spatio-temporal features of electroencephalography can be learned and realistic data can be generated. Experimental results show that this method outperforms other data augmentation techniques and improves the overall performance of motor imagery user action classification.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Computer Science, Interdisciplinary Applications
Yaser Ismail, Lei Wan, Jiayun Chen, Jianqiao Ye, Dongmin Yang
Summary: This paper introduces a robust ABAQUS plug-in called Virtual Data Generator (VDGen) for generating virtual data to identify uncertain material properties in unidirectional lamina through artificial neural networks (ANNs). The plug-in supports 3D finite element models and parameterizes the relationship between fiber mechanical properties and interphase parameters through ANN, facilitating the establishment of high-fidelity micromechanical finite element models.
ENGINEERING WITH COMPUTERS
(2022)
Article
Engineering, Civil
Qi Fan, Yang Xin, Bin Jia, Yang Zhang, Pinxiang Wang
Summary: In this paper, we propose a novel consortium blockchain-based trust model (COBATS) to achieve efficient and secure shared data storage and sharing in vehicular networks. We also design a trust management model to filter malicious recommendations and ensure high-quality data sharing among vehicles. Additionally, we present a consensus mechanism with joint PoS and PBFT to reduce resource consumption and improve the algorithm's efficiency. Simulation results demonstrate that COBATS can enhance the security and quality of data sharing and effectively handle certain attacks.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Environmental Sciences
Zheng Zhang, Zhe Yan, Jiankun Jing, Hanming Gu, Haiying Li
Summary: Deep-learning-based seismic data interpretation has gained significant attention. The current methods for obtaining training data, including synthesizing seismic data and manually labeling real data, have limitations. To address this, a label-to-data network based on cycle-consistent adversarial networks is proposed. This network generates synthetic seismic data that matches random labels and has similar features to real seismic data. Quantitative analysis and testing demonstrate the effectiveness and reliability of the generated data for seismic fault detection.